Aging simulation of human faces based on NMF with sparseness constraints

Authors:
Yong-Qing Ye;Ji-Xiang Du;Chuan-Min Zhai
Affiliations:
Department of Computer Science and Technology, Huaqiao University, Quanzhou;Department of Computer Science and Technology, Huaqiao University, Quanzhou and Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui;Department of Computer Science and Technology, Huaqiao University, Quanzhou
Venue:
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Year:
2010

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Abstract

As far as the majority of known aging methods are concerned, PCA (Principal Component Analysis) was used as the first step to extract facial features and build model space. In this paper, NMF (Non-negative Factorization) with sparseness constraints is used as an alternative to PCA in the feature extraction step when aging an unseen human face image to the required age. A variety of experiments demonstrate that by adding sparseness constraints to NMF we can get simulated aging faces which share more similarities with real images than those by the method of PCA, especially when we keep the coefficients sparse while leaving the basis vectors unconstrained.